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BFH-OST, a new predictive screening tool for identifying osteoporosis in postmenopausal Han Chinese women

Overview of attention for article published in Clinical Interventions in Aging, January 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (57th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

twitter
3 tweeters

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
32 Mendeley
Title
BFH-OST, a new predictive screening tool for identifying osteoporosis in postmenopausal Han Chinese women
Published in
Clinical Interventions in Aging, January 2016
DOI 10.2147/cia.s107675
Pubmed ID
Authors

Qi Fei, Zhao Ma, Yong YANG, JiSheng Lin, XiaoDong Zhang, Qian Meng, Bing-qiang WANG

Abstract

To develop a simple new clinical screening tool to identify primary osteoporosis by dual-energy X-ray absorptiometry (DXA) in postmenopausal women and to compare its validity with the Osteoporosis Self-Assessment Tool for Asians (OSTA) in a Han Chinese population. A cross-sectional study was conducted, enrolling 1,721 community-dwelling postmenopausal Han Chinese women. All the subjects completed a structured questionnaire and had their bone mineral density measured using DXA. Using logistic regression analysis, we assessed the ability of numerous potential risk factors examined in the questionnaire to identify women with osteoporosis. Based on this analysis, we build a new predictive model, the Beijing Friendship Hospital Osteoporosis Self-Assessment Tool (BFH-OST). Receiver operating characteristic curves were generated to compare the validity of the new model and OSTA in identifying postmenopausal women at increased risk of primary osteoporosis as defined according to the World Health Organization criteria. At screening, it was found that of the 1,721 subjects with DXA, 22.66% had osteoporosis and a further 47.36% had osteopenia. Of the items screened in the questionnaire, it was found that age, weight, height, body mass index, personal history of fracture after the age of 45 years, history of fragility fracture in either parent, current smoking, and consumption of three of more alcoholic drinks per day were all predictive of osteoporosis. However, age at menarche and menopause, years since menopause, and number of pregnancies and live births were irrelevant in this study. The logistic regression analysis and item reduction yielded a final tool (BFH-OST) based on age, body weight, height, and history of fracture after the age of 45 years. The BFH-OST index (cutoff =9.1), which performed better than OSTA, had a sensitivity of 73.6% and a specificity of 72.7% for identifying osteoporosis, with an area under the receiver operating characteristic curve of 0.797. BFH-OST may be a powerful and cost-effective new clinical risk assessment tool for prescreening postmenopausal women at increased risk for osteoporosis by DXA, especially for Han Chinese women.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 22%
Student > Bachelor 4 13%
Student > Doctoral Student 3 9%
Librarian 3 9%
Professor 2 6%
Other 5 16%
Unknown 8 25%
Readers by discipline Count As %
Medicine and Dentistry 8 25%
Nursing and Health Professions 7 22%
Pharmacology, Toxicology and Pharmaceutical Science 3 9%
Psychology 1 3%
Social Sciences 1 3%
Other 2 6%
Unknown 10 31%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 August 2016.
All research outputs
#3,599,934
of 8,307,635 outputs
Outputs from Clinical Interventions in Aging
#418
of 991 outputs
Outputs of similar age
#104,254
of 258,750 outputs
Outputs of similar age from Clinical Interventions in Aging
#21
of 55 outputs
Altmetric has tracked 8,307,635 research outputs across all sources so far. This one has received more attention than most of these and is in the 55th percentile.
So far Altmetric has tracked 991 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has gotten more attention than average, scoring higher than 54% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 258,750 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.